Les accidents de trotteur chez le nourrisson: à partir d'une étude prospective réalisée aux urgences pédiatriques du CHU de Nancy
Bibliographic record
Abstract
OBJECTIFS : etudier l'accidentologie du trotteur dans la tranche d'âge 5 a 15 mois en comparaison aux autres accidents domestiques. METHODE : mise en place d'un questionnaire relatif aux accidents de trotteur admis aux urgences pediatriques du CHU de Nancy, d'avril 2005 a mars 2006. RESULTATS : entre 5 et 15 mois, le trotteur est responsable de 15% des accidents domestiques (71/484). Ces accidents sont plus precoces, sont la premiere cause de chute dans les escaliers, de traumatismes crâniens legers et severes, et de traumatismes dentaires severes. On observe: 3 fractures de la boite crânienne, un volumineux hematome extradural compressif d'indication chirurgicale et deux brulures du 3eme degre ayant necessite une greffe. Le trotteur a ete reutilise plus d'une fois sur deux apres l'accident. CONCLUSION : le trotteur est source d'accidents nombreux et severes. Nous devons suivre l'exemple du Canada et interdire la fabrication et la vente du trotteur en France.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".